Master of Science – Data Analytics (MS-DA) program is a graduate program, in collaboration with the Departments of Computer Science, Economics, Mathematics, Industrial Management and Systems Engineering, Statistics, and Geography, focusing on using advanced technologies to manipulate big data, utilizing rigorous methods to interpret the data, and obtaining the business skills necessary to translate understanding into actionable organizational strategies.

Knowledge

  • demonstrate knowledge of big data management, predictive modeling using machine learning/statistical methods, and model validation and evaluation
  • demonstrate knowledge of analytics project requirements, data acquisition and visualization, and business communication/presentation

Skills :

  • demonstrate the ability to convert client’s business (or problem domain) into analytics project requirements

  • demonstrate the ability to collect data from social media and corporate databases, to assess data quality assessment, and provide analysis in terms of exploratory data analysis and data visualization
  • demonstrate the ability to clean and transform raw data sets for further data analytics processes
  • demonstrate the ability to use various machine learning algorithms (e.g., hierarchical clustering, association) & statistical modeling techniques (e.g., regression, classification) to the data, including feature engineering and parameter optimization 
  • demonstrate the ability to use proper model validation (e.g., cross validation) and evaluation methods and performance metrics (e.g., prediction accuracy)
  • demonstrate the ability to interpret model outputs, develop managerial and technical implications, and express oneself clearly, accurately, and professionally in both oral and written form

Students will be required to complete 30 hours of coursework: 21 hours of required and 9 hours of electives (Data Science track or Applied Analytics track).

Career Outcomes:

Graduates of the data analytics master’s program may enjoy careers as a:

  • data analyst
  • business intelligence analyst
  • market research analyst
  • analytics/management consultant
  • operations analyst
  • human resources analyst
  • product analyst
  • predictive analyst
  • quantitative analyst
  • data scientist
  • data engineer
  • data visualization specialist